How Close Are We To Artificial General Intelligence – And Do We Really Want To Go There?

How Close Are We To Artificial General Intelligence – And Do We Really Want To Go There?

Artificial Intelligence is something that’s been on the horizon for a long time – probably as long as anyone reading this will be able to remember.

Since its emergence into the public consciousness through science fiction, many have assumed that one day machines will have “general intelligence”, and pondered different practical, ethical and philosophical implications.

Today, though, there’s a palpable sense that we’re getting close and some, including several very smart people, are predicting that we are rushing headlong towards calamity.

But is this all marketing hype? Are we really any closer to generally intelligent machines than we were 20 years ago, when many of the ideas driving AI today – machine learning and deep learning, for example - already existed?

Well, to answer that question we have to first ask ourselves what really is this “intelligence”, that we are trying to simulate artificially.

Some of the most exciting recent work in AI, such as the development of deep neural networks, is intrinsically based around creating AIs which mimic the function of human brains. But human-like intelligence comes in many forms. We’re all aware of people who appear to be very smart in some ways, but less so in others. Some people might have a high IQ but poor social skills and limited ‘common sense’, while others could be successful entrepreneurs but have limited academic knowledge. AIs also vary wildly in the form of intelligence they emulate.

Defining “intelligence”

IQ tests were formulated as a method of quantifying intelligence, although their validity in this regard is often disputed. Machines can do IQ tests – with around the same ability level as a four-year-old. But there are many other factors which go into “human-like” intelligence that IQ tests do not even touch on.

Emotional intelligence registers how well someone is able to understand and interact with people on an emotional level, or interpret their own feelings. This is sometimes through of as something which is intuitive but is undoubtedly a mental process, dependent on our brain’s ability to analyse information and infer an insight or solution, so qualifies as “intelligence”. This aspect of our intelligence is thought to be integral to our creative abilities – something else machines will have to master if they are going to develop “human-like” intelligence. Steps are certainly being taken in this direction. The field of affective computing is all about training machines to become more emotionally intelligent and algorithms can already create music and even write poetry and novels.

Athletes and craftsmen rely on dexterity, hand-eye coordination and spatial awareness of what is going on around them as well as needing their brain to work quickly and accurately to react to complicated, changing circumstances. AI-powered robots have been taught to perform many complex physical tasks like walking, jumping or flying, and AI algorithms have learnt to play video games using only visual input, showing that they are capable of “learning” how to react to movement and even developing a desire to win.

Our communication skills – how well we are able to express our ideas and communicate our insights is another form of intelligence. Again, machines have made ground here, with recent developments in the AI-related fields of Natural Language Processing and Natural Language Generation (think of Amazon Alexa or Google Home), which are bringing them closer to being able to communicate with us in a human-like way.

An AI would have to be able to demonstrate all of these abilities, and probably many more, before it approached what we would consider to be a human-like level of intelligence. Now, undoubtedly, the building blocks are falling into place for this to become a reality, but is an artificial human brain, capable of working at super-speed and with unlimited memory and perfect recollection, what we want or need?

Artificial consciousness

The question has ethical implications, particularly if we bring the controversial topic of consciousness into the equation. From a scientific viewpoint, consciousness is a state that arises when a biological brain interprets the flood of sensory input streaming in from the world around it, leading, somehow, to the conclusion that it exists as an entity.

It’s not well understood at all – but most of us can conceive how this massive flood of images and sounds is interpreted through a biological neuro-network which leads to “thoughts” – and among those thoughts are concepts of individual existence such as “I am a human”, “I exist” and “I am experiencing thoughts”.

So, it’s only a small step of logic to assume that machines will one day – perhaps soon, given how broad the stream of data they are capable of ingesting and processing is becoming – in some way experience this phenomena, too. How long before a machine is capable of saying to us “I too, am experiencing a sense of existence and individuality”? And, when it does, will we have any sound intellectual ground from which to argue that it is isn’t? After all, science has yet to put forward any evidence against the idea that we are entirely mechanistic constructs ourselves. Our brains run on electricity and rely on energy to fuel them.

You might also want to look at this topic through a religious lens. If your view is that there is a God that created us, doesn’t that mean that we’re really nothing more than AIs ourselves? Giving us even less ground to argue with a human-created AI that it isn’t sentient itself?

Today, when we talk about consciousness and the possibility that machines will develop sentience, it feels like we are wandering into fringe territories. But it’s potentially a problem that will become very real for us at some time in the future, if we remain in pursuit of giving machines ever-more human-like intelligence.

Perhaps fortunately, when we talk about AI today, most of the time we are talking about very specific applications focused on solving a particular problem. It’s doubtful, for example, that we are going to find ourselves in an argument any time soon with the AI that manages energy usage in Google’s datacentres about whether it is conscious or not. But that could just be because we haven’t given it a mouth to speak with yet, or the sensors it needs to make that deduction. When we do, we might have to prepare for that event.

Bernard Marr is a bestselling author, keynote speaker, and advisor to companies and governments. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topics of intelligent business performance for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation have millions of readers.